Computational Investigation on Collective Dynamical Behaviors of Flickering Laminar Buoyant Diffusion Flames in Circular Arrays

The emergence of collective dynamical behaviors in a complex system has distinct properties that its individuals do not have on their own. In the study, a series of circular arrays of octuple flickering laminar buoyant diffusion flames were computationally investigated to understand their collective behaviors. Five distinct dynamical modes, such as the merged, in-phase mode, rotation, flickering death, partially flickering death, and anti-phase modes, were identified and interpreted from the perspective of vortex dynamics. All the modes were found to be controlled by the three dimensionless parameters, namely the normalized flame frequency f/f_0, the ratio of the flame separation distance to the flame diameter, and the Grashof number Gr. A unified regime diagram was obtained in terms of f/f_0 and of a combined Reynolds-number-like parameter. In addition, the bifurcation transition from the in-phase mode and the anti-phase mode to the totally or partially flickering death occurs at 620+-50.Comment: research paper (14 pages, 9 figures) with supplementary material (7 pages, 3 tables, 5 figures

Numerical study of the development and angular speed of a small-scale fire whirl

The development stages of a small-scale fire whirl including the ignition, flame-rising and fully-developed whirling were successfully captured by a fire field model. Good agreements between simulation and experimental results for vertical temperature profiles and flame height were achieved. With the consideration of the interaction between the liquid and gas phases of the fuel, the radiation heat feedback towards the liquid fuel was aptly predicted. Angular velocities that govern the rotational motion of the fire whirl were evaluated based on computed data. Furthermore, the circulate motion and buoyancy force promoting the extension of flame height were characterised in numerical simulations

Numerical study of the development and angular speed of a small-scale fire whirl

The development stages of a small-scale fire whirl including the ignition, flame-rising and fully-developed whirling were successfully captured by a fire field model. Good agreements between simulation and experimental results for vertical temperature profiles and flame height were achieved. With the consideration of the interaction between the liquid and gas phases of the fuel, the radiation heat feedback towards the liquid fuel was aptly predicted. Angular velocities that govern the rotational motion of the fire whirl were evaluated based on computed data. Furthermore, the circulate motion and buoyancy force promoting the extension of flame height were characterised in numerical simulations

Critical assessment of particle-infused fire suppression system in building structures

In the past decades, water droplet-based suppression systems (i.e. fire sprinklers, water mist) have been extensively utilized as building fire suppression systems. Nevertheless, current suppression systems operate under considerable design limitations due to high-rise structures and rapid increase in building complexity, such as pressure supply and water storages. Challenges can also be foreseen in suppressing water-reactive chemicals (i.e. alkali metals, hydrides) as the violent explosive reaction will be triggered. Therefore, it is vital to investigate potential suppression agents to cope with the increasing building fire risk associated with complex building materials and hazardous combustibles. A large eddy simulation (LES) model incorporated with novel user-defined functions (UDFs) to consider particle expansion and charring was proposed in this thesis. This model has been utilised to numerically study an experimental case to investigate the fire suppression behaviour of expandable graphite (EG) in building structures. This approach has provided an in-depth characterization of EG's thermophysical properties. This includes the expansion, barrier effect from char formation and the decomposition of EG. It was discovered that EG is more effective in fire suppression compared to natural graphite. Among the diameter range of EG (400 µm - 1000 µm), the smaller diameter of EGs tend to be efficient in suppressing metallic fire. The WALE SGS model has provided the most accurate temperature prediction among other SGS models, with average relative errors of 7.71% and 8.93%. The novel multiphase model was comprehensively validated by material testing and other experiments, and proven to be an effective tool to investigate particle-infused suppression in a structural fire. Moreover, the thermophysical properties (i.e. pyrolysis kinetics) of graphite have also been characterized through Molecular Dynamics (MD) simulations. The extracted Arrhenius kinetics parameters (i.e. activation energy) were compared to the experimental results, with an averaged relative discrepancy between 1.71 % - 5.38 %. The species breakdown analysis from the ReaxFF simulation will also further explore the feasibility of MD as a practical approach to analyse graphite's pyrolysis and chemical reaction mechanisms. The MD simulations have improved the understanding of particle pyrolysis and volatile emission during the oxidation of graphite and provided insights into the future of multiscale simulations

Numerical Analysis of Lithium-ion Battery Thermal Management System Towards Fire Safety Improvement

The development of alternative energy sources aims to tackle the energy crisis and climate change. Due to the intermittent nature of renewable energy, energy storage systems find antidotes to the current flaws for ensuring a stable and consistent power supply and reducing our reliance on fossil fuels. Lithium-ion batteries are the most used energy storage unit and have been applied in many fields, such as portable devices, building infrastructure, automotive industries, etc. Nevertheless, there remain significant safety concerns and fire risks. Thus, this has created much interest particularly in developing a comprehensive numerical tool to effectively assess the thermal behaviour and safety performance of battery thermal management systems (BTMs). In this thesis, a modelling framework was built by integrating the artificial neural network model with the computational fluid dynamics analysis. This includes (i) a comparison of natural ventilation and forced air cooling under various ambient pressures; (ii) an analysis of thermal behaviour and cooling performance with different ambient temperatures and ventilation velocities; and (iii) optimisation of battery pack layout for enhancing the cooling efficiency and reducing the risks of thermal runaway and fire outbreak. The optimal battery design achieved a 1.9% decrease in maximum temperature and a 4.5% drop in temperature difference. Moreover, this thesis delivered an overall review of BTMs employing machine learning (ML) techniques and the application of various ML models in battery fire diagnosis and early warning, which brings new insights into BTMs design and anticipates further smart battery systems. In addition, the battery thermal propagation effect under various abnormal heat generation locations was demonstrated to investigate several stipulating thermal propagation scenarios for enhancing battery thermal performances. The results indicated that various abnormal heat locations disperse heat to the surrounding coolant and other cells, affecting the cooling performance of the battery pack. The feasibility of compiling all pertinent information, including battery parameters and operation conditions, was studied in this thesis since ML models can build non-related factors relationships. The integrated numerical model offers a promising and efficient tool for simultaneously optimising multiple factors in battery design and facilitates a constructive understanding of battery performance and potential risks

Multi-scale Fire Modelling of Combustible Building Materials

The utilisation of lightweight polymers in building materials has come under tremendous scrutiny, driven by the numerous high-profile fire incidents (e.g., Grenfell Tower UK, 2017) and heightened public awareness of highly combustible materials in the past decade. Consequently, this creates significant interest in developing robust numerical tools to effectively assess the fire behaviours and toxicity of these combustible materials and establish safe use guidelines. In this dissertation, a modelling framework has been developed incorporating multi-scale computational techniques that capture and couple the thermal degradation and combustion characteristics of building materials. This includes (i) characterisation of essential pyrolysis kinetics from thermogravimetric analysis (TGA) via machine learning aided algorithm; (ii) in-depth pyrolysis breakdown from molecular dynamics (MD) simulations coupled with reactive force fields (ReaxFF); and (iii) Computational Fluid Dynamics (CFD) pyrolysis model involving char formation, moving boundary surface tracking and gas-phase combustion considering detailed chemical reaction mechanisms and soot particle formation. The framework was adopted to assess the fire performance of a selection of FR/non-FR building materials. For the first time, the composition of char formations for the selective polymers was predicted by the MD simulation by analysing the accumulation of pure carbon chain compounds. The extracted pyrolysis kinetics achieved accurate fits with the experimental data. Furthermore, the application of MD allowed the characterisation of the full distribution of volatile and toxic gas species without substantial prior knowledge or experimental testing. The realised pyrolysis inputs were applied in the CFD model for cone calorimeter simulations, which yielded good agreement with experiments in terms of heat release, ignition time and burning duration. With the incorporation of solid interface tracking and char formation, the model was able to predict the thermal degrading solid surface and capture the prolonged burn duration. The char formation acts as a thermal layer to protect the unburnt virgin material from heat penetration during the pyrolysis process. Furthermore, with the application of detailed chemical kinetics for combustion and soot formation reaction mechanisms, the fire model was able to aptly predict the generation of asphyxiant gas such as CO and CO2 during the burning process